Skip to contents

Changelog

Source: NEWS.md

baselinr 0.5.0

CRAN release: 2026-06-30

  • New wwc_summary(): collapse a baseline_equivalence() table into an overall WWC verdict (satisfied / satisfied_with_adjustment / not_satisfied) plus per-category counts and the largest absolute effect size.
  • New attrition(): overall and differential attrition for a two-group design, the inputs to the WWC attrition standard.

baselinr 0.4.0

  • New bundled dataset tutoring: a simulated quasi-experimental tutoring evaluation (400 students) whose covariates span all three WWC equivalence categories. See data-raw/tutoring.R for how it is generated.
  • New vignette “An impact-evaluation workflow” walking from raw study data to a baseline-equivalence report, Love plot, and formatted table.

baselinr 0.3.0

  • New love_plot(): a Love plot of standardized effect sizes across covariates, with WWC threshold reference lines and points coloured by category (requires ggplot2).
  • New gt_baseline(): render a baseline equivalence table as a formatted gt table with readable labels and rounded statistics (requires gt).
  • ggplot2 and gt added to Suggests; both functions error gracefully if the package is not installed.

baselinr 0.2.0

  • New cox_index(): WWC Cox index standardized effect size for binary (dichotomous) covariates.
  • baseline_equivalence() now handles binary covariates (numeric 0/1, logical, or two-level factor) via the Cox index, in addition to continuous covariates via Hedges’ g. A covariate with exactly two unique values is treated as binary.
  • The output gains a type column ("continuous" / "binary"), and the effect-size column is renamed from hedges_g to the estimator-agnostic effect_size (breaking change). For binary covariates, mean_treatment and mean_comparison report event proportions.
  • The default covariate set now includes logical and factor columns, not only numeric ones.

Roadmap

  • Formatted output for reports (gt / flextable).
  • Love plot of standardized effect sizes across covariates.

baselinr 0.1.0

Initial scaffold.

  • hedges_g(): standardized mean difference (Hedges’ g) between a treatment and a comparison group, with the WWC small-sample correction factor.
  • wwc_classify(): classify standardized mean differences into the three WWC baseline-equivalence categories.
  • baseline_equivalence(): build a report-ready baseline equivalence table for continuous covariates.